Introduction to Light Detection and Ranging (LiDAR) feature image Source: National Ecological Observatory Network (NEON)
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Series: Introduction to Light Detection and Ranging (LiDAR)

About

The tutorials in this series introduces Light Detection and Ranging (LiDAR).
Concepts covered include how LiDAR data is collected, LiDAR as gridded, raster data and an introduction to digital models derived from LiDAR data (Canopy Height Models (CHM), Digital Surface Models (DSM), and Digital Terrain Models (DTM)). The series introduces the concepts through videos, graphical examples, and text. The series continues with visualization of LiDAR-derived raster data using plas.io, plot.ly and R, three free, open-source tools.

Data used in this series are from the National Ecological Observatory Network (NEON) and are in .las, GeoTiff and .csv formats.

Series Goals / Objectives

After completing the series you will:

  • Know what LiDAR data are
  • Understand key attributes of LiDAR data
  • Know what LiDAR-derived DTM, DSM, and CHM digital models are
  • Be able to visualize LiDAR-derived data in .las format using plas.io
  • Be able to create a Canopy Height Model in R
  • Be able to create an interactive plot.ly map of LiDAR-derived data

Things You’ll Need To Complete This Series

Setup RStudio

To complete some of the tutorials in this series, you will need an updated version of R and, preferably, RStudio installed on your computer.

R is a programming language that specializes in statistical computing. It is a powerful tool for exploratory data analysis. To interact with R, we strongly recommend RStudio, an interactive development environment (IDE).

Download Data

Data is available for download in those tutorials that focus on teaching data skills.


Set Working Directory: This lesson assumes that you have set your working directory to the location of the downloaded and unzipped data subsets. An overview of setting the working directory in R can be found here.

R Script & Challenge Code: NEON data lessons often contain challenges that reinforce learned skills. If available, the code for challenge solutions is found in the downloadable R script of the entire lesson, available in the footer of each lesson page.

Tutorials in Workshop Series